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ARS Home » Plains Area » Lincoln, Nebraska » Wheat, Sorghum and Forage Research » Research » Publications at this Location » Publication #374246

Research Project: Improving Forage and Bioenergy Plants and Production Systems for the Central U.S.

Location: Wheat, Sorghum and Forage Research

Title: Comparing the use of handheld and benchtop NIR spectrometers in predicting nutritional value of forage

item RUKUNDO, ISSAC - University Of Nebraska
item DANAO, MARY-GRACE - University Of Nebraska
item Mitchell, Robert - Rob
item Masterson, Steven
item WELLER, CURTIS - University Of Nebraska

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2020
Publication Date: 2/2/2021
Citation: Rukundo, I., Danao, M., Mitchell, R., Masterson, S.D., Weller, C. 2021. Comparing the use of handheld and benchtop NIR spectrometers in predicting nutritional value of forage. Applied Engineering in Agriculture. 37(1):171-181.

Interpretive Summary: Switchgrass is a high-yielding perennial warm-season grass with a high relative feed value for use as cattle forage within a recommended maturity window. Beyond the grazing period, the nutritional quality of switchgrass declines with maturity, as the crop becomes fibrous and less palatable. Forage quality is routinely assessed using laboratory methods based on chemical composition and in vitro dry matter digestibility (IVDMD). Near infrared (NIR) spectroscopy provides a rapid, reliable, non-destructive technique for determining the nutritive value of forages. NIR spectroscopy is used regularly to predict forage composition using laboratory benchtop NIR systems. Portable, handheld NIR spectrometers are available that provide rapid data collection and analysis at low cost. Our objective was to compare the performance of two handheld NIR spectrometers to two benchtop NIR systems to predict nitrogen (N), acid detergent fiber (ADF), neutral detergent fiber (NDF), and acid detergent lignin (ADL) contents, as well as IVDMD for switchgrass. The predictive values of the handheld units for N and IVDMD were similar to the benchtop units, but the primary fiber components of ADF, NDF, and ADL were poorly predicted. The handheld devices are very effective for screening switchgrass samples for N and IVDMD, but predicting fiber components was ineffective. Predicting N and IVDMD with the handheld devices provides a valuable, low cost solution for estimating the nutritive value of switchgrass forage.

Technical Abstract: Assessing the nutritional composition of animal feed and forage materials is important to achieve high animal productivity and wellness. Precision nutrition programs that use NIR technology can determine the nutritional composition of feed and forage quickly and simply, generating actionable information such as total nitrogen (N), acid detergent fiber (ADF), neutral detergent fiber (NDF), and acid detergent lignin (ADL) contents, as well as in vitro dry matter digestibility (IVDMD). Recent advances in optics and microelectronics have allowed for the development of handheld spectrometers that are portable, robust, and user-friendly. However, are the handheld units accurate enough to predict nutritional content of animal feed? In this study, the performance of two handheld NIR spectrometers to predict the nutritional content of forage based on N, ADF, NDF, ADL, and IVDMD was evaluated by comparing them to two benchtop NIR spectrometers often used in feed and forage analysis. The forage samples comprised switchgrass (Panicum virgatum L), big bluestem (Andropogon gerardi), and Indiangrass (Sorghastrum nutans). The first handheld spectrometer covers 780-2500 nm with a spectral interval (??) of 1 nm, while the second handheld spectrometer is a palm-sized smartphone spectrometer covering 900-1700 nm with ?? = 4 nm. The benchtop spectrometers both cover 400-2500 nm with ?? = 2 nm. Forage samples were scanned on each spectrometer and divided into calibration (n = 143) and validation (n = 35) sets. Partial least squares (PLS) regression was used to calibrate all spectrometers using mean-centered spectral data that had been preprocessed using Savitzky-Golay first derivative (SG1) or second derivative (SG2) algorithm with 9-63 smoothing points. Results showed that PLS models that best predicted N using the benchtop spectrometers had lower standard error of prediction (SEP = 1.24-1.28 g kg-1) and higher ratio of prediction to deviation (RPD = 3.66-3.78) compared to the models developed based on spectra collected from the handheld spectrometers (SEP = 1.46-1.78 g kg-1; RPD = 2.39-2.84). ADF, NDF, and ADL were variable and generally poorly predicted using spectra from the benchtop spectrometers (SEP = 10.02-33.19 g kg-1;RPD = 1.71-2.24), and even more so using the handheld spectrometers (SEP = 10.63-32.57 g kg-1;RPD = 1.64-2.47). Predicting IVDMD was similar for both sets of benchtop (SEP = 40.00-41.73 g kg-1; RPD = 2.24-2.34) and handheld (SEP = 34.46-40.84 g kg-1; RPD = 2.29-2.72) spectrometers. These results show that the handheld devices can be used for screening of forage samples based on N, which is a closely monitored component in animal feed and forage, as well as IVDMD, an important forage quality index.